Cyvl AI Engineer at Cyvl develops computer vision and 3D perception models from LiDAR and imagery to assess infrastructure. The role includes building LLM-powered products and owning models from training to production deployment.
Responsibilities
Cyvl has one of the largest proprietary datasets of US infrastructure: LiDAR and imagery from hundreds of cities. As an AI Engineer, you'll turn that data into intelligence, from computer vision models that detect and assess assets to LLM-powered agents and tools that let customers and partners ask questions of the physical world. You'll work from prototype to production, shipping models and AI features customers use every day. This role is based in Somerville, MA, or remote from San Francisco, CA.
Build and improve computer vision and 3D perception models that detect, classify, and assess infrastructure (pavement, signs, sidewalks, trees) from LiDAR and imagery.
Build LLM-powered products: agentic workflows, our MCP server, and AI copilots that put Cyvl data to work inside customer tools.
Own models from data and training through evaluation, deployment, and monitoring in production.
Design evaluation sets and metrics that tie model performance to what customers actually need.
Stay close to the state of the art and bring the right new tools into our products and our own workflows.
3+ years building and shipping ML or AI systems in production
Strong Python and a modern deep learning framework (PyTorch preferred)
Hands-on experience with computer vision, 3D perception, or LLM applications (RAG, tool use, agents, evals)
Solid software engineering fundamentals: testing, code review, and cloud deployment
Ability to go from an ambiguous problem to a working prototype quickly, then make it production-grade
Qualification
Model Context Protocol (MCP)Geospatial or remote sensing backgroundMLOpsAdvanced degree in CSHard techHard problems in the real worldOwnership that compounds
Required
3+ years building and shipping ML or AI systems in production
Strong Python and a modern deep learning framework (PyTorch preferred)
Hands-on experience with computer vision, 3D perception, or LLM applications
Solid software engineering fundamentals including testing, code review, and cloud deployment
Ability to go from ambiguous problem to working prototype quickly and make it production-grade
Preferred
Point cloud or multimodal work (LiDAR and imagery fusion)
Model Context Protocol (MCP), foundation model APIs, or agent frameworks
Geospatial or remote sensing background
MLOps: model serving, GPU infrastructure, experiment tracking
Advanced degree in CS, ML, robotics, or a related field, or equivalent experience
Hard tech. Real streets. Your name on it.
Hard problems in the real world. You build end-to-end: our own hardware, software and AI, with work that shows up on the street in the real world.
Ownership that compounds. You own outcomes, not tasks. You work directly with customers and across our team, and you'll own more, sooner, than almost anywhere else.
